Currently there is no automatic mechanism for eliminating the generation of
features that are not selected downstream. It needs to be achieved manually.
On 15 March 2016 at 08:05, Philip Tully <tu...@csc.kth.se> wrote:
> Hi,
>
> I'm trying to optimize the time it takes to make a prediction with my
> model(s). I realized that when I perform feature selection during the
> model fit(), that these features are likely still computed when I go
> to predict() or predict_proba(). An optimization would then involve
> actually eliminating those features that aren't selected from my
> Pipeline altogether, instead of just selecting them.
>
> Does sklearn already do this automatically? Or does this readjustment
> need to be done manually before serialization?
>
> thanks,
> Philip
>
>
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